The marketing organization’s journey to become data-driven

Debra Zahay, Debika Sihi, Laurent Muzellec, Devon S. Johnson

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

Purpose: This paper aims to improve understanding of data-driven marketing by examining the experiences of managers implementing big data analytics in the marketing function. Through a series of research questions, this exploratory study seeks to define what big data analytics means in marketing practice. It also seeks to uncover the challenges and identifiable stages of big data analytics implementation. Design/methodology/approach: A total of 15 open-ended in-depth interviews were conducted with marketing and analytics executives in a variety of industries in Ireland and the USA. Interview transcripts were subjected to open coding and axial coding to address the research questions. Findings: The study reveals that managers consider marketing big data analytics to be a series of tools and capabilities used to inform product innovation and marketing strategy-making processes and to defend the brand against emerging risks. Additionally, the study reveals that big data analytics implementation is championed at different organizational levels using different types of dynamic learning capabilities, contingent on the champion’s stature within the organization. Originality/value: From the qualitative analysis, it is proposed that marketing departments undergo five stages of big data analytics implementation: sprouting, recognition, commitment, culture shift and data-driven marketing. Each stage identifies the key characteristics and potential pitfalls to be avoided and provides advice to marketing managers on how to implement big data analytics.

Original languageEnglish
Pages (from-to)162-178
Number of pages17
JournalJournal of Research in Interactive Marketing
Volume13
Issue number2
DOIs
StatePublished - 10 Jun 2019

Keywords

  • Business intelligence
  • Customer analytics
  • Customer data management
  • Data analytics
  • Data mining

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